T. Trevor Caughlin

Loss of animal seed dispersal increases extinction risk in a tropical tree species due to pervasive negative density dependence across life stages

Overhunting in tropical forests reduces populations of vertebrate seed dispersers. If reduced seed dispersal has a negative impact on tree population viability, overhunting could lead to altered forest structure and dynamics, including decreased biodiversity. However, empirical data showing decreased animal-dispersed tree abundance in overhunted forests contradict demographic models which predict minimal sensitivity of tree population growth rate to early life stages. One resolution to this discrepancy is that seed dispersal determines spatial aggregation, which could have demographic consequences for all life stages. We tested the impact of dispersal loss on population viability of a tropical tree species, Miliusa horsfieldii, currently dispersed by an intact community of large mammals in a Thai forest. We evaluated the effect of spatial aggregation for all tree life stages, from seeds to adult trees, and constructed simulation models to compare population viability with and without animal-mediated seed dispersal. In simulated populations, disperser loss increased spatial aggregation by fourfold, leading to increased negative density dependence across the life cycle and a 10-fold increase in the probability of extinction. Given that the majority of tree species in tropical forests are animal-dispersed, overhunting will potentially result in forests that are fundamentally different from those existing now.

Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data

Humans move frequently and tend to carry parasites among areas with endemic malaria and into areas where local transmission is unsustainable. Human-mediated parasite mobility can thus sustain parasite populations in areas where they would otherwise be absent. Data describing human mobility and malaria epidemiology can help classify landscapes into parasite demographic sources and sinks, ecological concepts that have parallels in malaria control discussions of transmission foci. By linking transmission to parasite flow, it is possible to stratify landscapes for malaria control and elimination, as sources are disproportionately important to the regional persistence of malaria parasites. Here, we identify putative malaria sources and sinks for pre-elimination Namibia using malaria parasite rate (PR) maps and call data records from mobile phones, using a steady-state analysis of a malaria transmission model to infer where infections most likely occurred. We also examined how the landscape of transmission and burden changed from the pre-elimination setting by comparing the location and extent of predicted pre-elimination transmission foci with modeled incidence for 2009. This comparison suggests that while transmission was spatially focal pre-elimination, the spatial distribution of cases changed as burden declined. The changing spatial distribution of burden could be due to importation, with cases focused around importation hotspots, or due to heterogeneous application of elimination effort. While this framework is an important step towards understanding progressive changes in malaria distribution and the role of subnational transmission dynamics in a policy-relevant way, future work should account for international parasite movement, utilize real time surveillance data, and relax the steady state assumption required by the presented model.

Urbanized landscapes favored by fig‐eating birds increase invasive but not native juvenile strangler fig abundance

Propagule pressure can determine the success or failure of invasive plant range expansion. Range expansion takes place at large spatial scales, often encompassing many types of land cover, yet the effect of landscape context on propagule pressure remains largely unknown. Many studies have reported a positive correlation between invasive plant abundance and human land use; increased propagule pressure in these landscapes may be responsible for this correlation. We tested the hypothesis that increased rates of seed dispersal by fig-eating birds, which are more common in urban habitats, result in an increase in invasive strangler fig abundance in landscapes dominated by human land use. We quantified abundance of an invasive species (Ficus microcarpa) and a native species (F. aurea) of strangler fig in plots spanning the entire range of human land use in South Florida, USA, from urban parking lots to native forest. We then compared models that predicted juvenile fig abundance based on distance to adult fig seed sources and fig-eating bird habitat quality with models that lacked one or both of these terms. The best model for juvenile invasive fig abundance included both distance to adult and fig-eating bird habitat terms, suggesting that landscape effects on invasive fig abundance are mediated by seed-dispersing birds. In contrast, the best model for juvenile native fig abundance included only presence/absence of adults, suggesting that distance from individual adult trees may have less effect on seed limitation for a native species compared to an invasive species undergoing range expansion. However, models for both species included significant effects of adult seed sources, implying that juvenile abundance is limited by seed arrival. This result was corroborated by a seed addition experiment that indicated that both native and invasive strangler figs were strongly seed limited. Understanding how landscape context affects the mechanisms of plant invasion may lead to better management techniques. Our results suggest that prioritizing removal of adult trees in sites with high fig-eating bird habitat may be the most effective method to control F. microcarpa abundance.

When does seed limitation matter for scaling up reforestation from patches to landscapes

Restoring forest to hundreds of millions of hectares of degraded land has become a centerpiece of international plans to sequester carbon and conserve biodiversity. Forest landscape restoration will require scaling up ecological knowledge of secondary succession from small-scale field studies to predict forest recovery rates in heterogeneous landscapes. However, ecological field studies reveal widely divergent times to forest recovery, in part due to landscape features that are difficult to replicate in empirical studies. Seed rain can determine reforestation rate and depends on landscape features that are beyond the scale of most field studies. We develop mathematical models to quantify how landscape configuration affects seed rain and forest regrowth in degraded patches. The models show how landscape features can alter the successional trajectories of otherwise identical patches, thus providing insight into why some empirical studies reveal a strong effect of seed rain on secondary succession, while others do not. We show that seed rain will strongly limit reforestation rate when patches are near a threshold for arrested succession, when positive feedbacks between tree canopy cover and seed rain occur during early succession, and when directed dispersal leads to between-patch interactions. In contrast, seed rain has weak effects on reforestation rate over a wide range of conditions, including when landscape-scale seed availability is either very high or very low. Our modeling framework incorporates growth and survival parameters that are commonly estimated in field studies of reforestation. We demonstrate how mathematical models can inform forest landscape restoration by allowing land managers to predict where natural regeneration will be sufficient to restore tree cover. Translating quantitative forecasts into spatially targeted interventions for forest landscape restoration could support target goals of restoring millions of hectares of degraded land and help mitigate global climate change.

Spatial Heterogeneity, Host Movement and Mosquito-Borne Disease Transmission

Mosquito-borne diseases are a global health priority disproportionately affecting low-income populations in tropical and sub-tropical countries. These pathogens live in mosquitoes and hosts that interact in spatially heterogeneous environments where hosts move between regions of varying transmission intensity. Although there is increasing interest in the implications of spatial processes for mosquito-borne disease dynamics, most of our understanding derives from models that assume spatially homogeneous transmission. Spatial variation in contact rates can influence transmission and the risk of epidemics, yet the interaction between spatial heterogeneity and movement of hosts remains relatively unexplored. Here we explore, analytically and through numerical simulations, how human mobility connects spatially heterogeneous mosquito populations, thereby influencing disease persistence (determined by the basic reproduction number R 0), prevalence and their relationship. We show that, when local transmission rates are highly heterogeneous, R 0 declines asymptotically as human mobility increases, but infection prevalence peaks at low to intermediate rates of movement and decreases asymptotically after this peak. Movement can reduce heterogeneity in exposure to mosquito biting. As a result, if biting intensity is high but uneven, infection prevalence increases with mobility despite reductions in R 0. This increase in prevalence decreases with further increase in mobility because individuals do not spend enough time in high transmission patches, hence decreasing the number of new infections and overall prevalence. These results provide a better basis for understanding the interplay between spatial transmission heterogeneity and human mobility, and their combined influence on prevalence and R 0.

Combining mesocosm and field experiments to predict invasive plant performance: a hierarchical Bayesian approach

Invasive plant fecundity underlies propagule pressure and ultimately range expansion. Predicting fecundity across large spatial scales, from regions to landscapes, is critical for understanding invasion dynamics and optimizing management. However, to accurately predict fecundity and other demographic processes, improved models that scale individual plant responses to abiotic drivers across heterogeneous environments are needed. Here we combine two experimental data sets to predict fecundity of a widespread and problematic invasive grass over large spatial scales. First, we analyzed seed production as a function of plant biomass in a small-scale mesocosm experiment with manipulated light levels. Then, in a field introduction experiment, we tracked plant performance across 21 common garden sites that differed widely in available light and other factors. We jointly analyzed these data using a Bayesian hierarchical model (BHM) framework to predict fecundity as a function of light in the field. Our analysis reveals that the invasive species is likely to produce sufficient seed to overwhelm establishment resistance, even in deeply shaded environments, and is likely seed-limited across much of its range. Finally, we extend this framework to address the general problem of how to scale up plant demographic processes and analyze the factors that control plant distribution and abundance at large scales.

Place-based attributes predict community membership in a mobile phone communication network.

Social networks can be organized into communities of closely connected nodes, a property known as modularity. Because diseases, information, and behaviors spread faster within communities than between communities, understanding modularity has broad implications for public policy, epidemiology and the social sciences. Explanations for community formation in social networks often incorporate the attributes of individual people, such as gender, ethnicity or shared activities. High modularity is also a property of large-scale social networks, where each node represents a population of individuals at a location, such as call flow between mobile phone towers. However, whether or not place-based attributes, including land cover and economic activity, can predict community membership for network nodes in large-scale networks remains unknown. We describe the pattern of modularity in a mobile phone communication network in the Dominican Republic, and use a linear discriminant analysis (LDA) to determine whether geographic context can explain community membership. Our results demonstrate that place-based attributes, including sugar cane production, urbanization, distance to the nearest airport, and wealth, correctly predicted community membership for over 70% of mobile phone towers. We observed a strongly positive correlation (r = 0.97) between the modularity score and the predictive ability of the LDA, suggesting that place-based attributes can accurately represent the processes driving modularity. In the absence of social network data, the methods we present can be used to predict community membership over large scales using solely place-based attributes.

Disentangling fragmentation effects on herbivory in understory plants of longleaf pine savanna

Habitat fragmentation affects species and their interactions through intertwined mechanisms that include changes to fragment area, shape, connectivity and distance to edge. Disentangling these pathways is a fundamental challenge of landscape ecology and will help identify ecological processes important for management of rare species or restoration of fragmented habitats. In a landscape experiment that manipulated connectivity, fragment shape, and distance to edge while holding fragment area constant, we examined how fragmentation impacts herbivory and growth of nine plant species in longleaf pine savanna. Probability of herbivory in open habitat was strongly dependent on proximity to forest edge for every species, increasing with distance to edge in six species (primarily grasses and annual forbs) and decreasing in three species (perennial forbs and a shrub). In the two species of perennial forbs, these edge effects were dependent on fragment shape; herbivory strongly decreased with distance to edge in fragments of two shapes, but not in a third shape. For most species, however, probability of herbivory was unrelated to connectivity or fragment shape. Growth was generally determined more strongly by leaf herbivory than by distance to edge, fragment shape, or connectivity. Taken together, these results demonstrate consistently strong edge effects on herbivory, one of the most important biotic factors determining plant growth and demography. Our results contrast with the generally inconsistent results of observational studies, likely because our experimental approach enabled us to tease apart landscape processes that are typically confounded.